These are just a scant few of the common questions asked by bioinformatics students as they ready themselves for the next exam sitting. If you read the entire Syllabus (and I know that everyone does), you will see a section devoted to study and exam techniques. The section discusses such broad concepts as motivation, scheduling, and retention. Upon reading this section, however, I find the "hints" to be too general. Much of the advice boils down to read, study, understand, and memorize the material. The techniques mentioned apply to everyone and thus the overall advice ends up as a broad overview of the learning process.

The idea behind this article is to give students ideas on different approaches and techniques in the preparation for exams. By providing various ways to prepare for the exam process, fascinated readers may gain some additional insight to help complement their studying methodology. There are, of course, many common themes expressed in this small empirical sample of students' study habits. The idea of note cards, memorization, and problem solving are frequently mentioned by all students. No matter what technique a candidate uses, it always takes a significant amount of time and personal resources to successfully complete the examination process.

1 Explain it in your own word

Your teacher or lecturer can explain something to you, you can learn it from a text book, your friends can study with you, even your own notes can explain it to you but all these explanations are of little use if, by the end, you can’t explain what you have learned to yourself. The BINC exam looking for ability to write and explain the concept in your own word. You, therefore, need to illustrate in an exam to get top exam results, then you won’t be happy with your end exam result. So don’t just memorise and tick off the list – make sure you understand your theory.

2 Be an examiner yourself

Of course, depending on what you’re studying, it may be quite difficult to get into a position to understand a concept, theory or other information you need to learn. Ask ‘stupid’ question to yourself and train yourself for the worst! Embrace your curiosity, for as William Arthur Ward said: “Curiosity is the wick in the candle of learning.” Doing so will allow you to fill in the blanks and better prepare you for exams.

3 Quiz yourself

Once you feel you understand topic, it is important to test yourself regularly. Try yourself to replicate exam conditions as much as possible: turn your phone off, don’t talk, time yourself etc. You can set yourself a study quiz or practice exam questions and, so long as you approach it with the right mindset, you can get a very good idea of how much you know. You gain a greater insight into where you stand in relation to what you’ve studied so far.

4 Online study

Keeping the fact that, bioinformatics is ever changing subject, you might need to update yourself on timely basis. Don’t feel obliged to just sit in front of a book with a highlighter; there are many different ways to improve your bioinformatics knowledge. Login and check almost all web servers and keep yourself updated, like how many genomes sequenced, sizes, techniques used, software names etc.

5 Study plan

In order to achieve exam success, you need to know what you want to achieve and focus on. That’s why it is extremely important to set your Study Goals now and outline to yourself what you need to do. With your study goals in mind, you properly need to attention all subjects. It should be broad enough to allow you to add and change aspects but concise enough so you know you’re covering each subject/topic as best you can at this point.

Address of the bookmark: http://pasapipeline.github.io/

Find out more on our blog:
http://www.ensembl.info/…/find-predicted-crispr-sites-usin…/

August 17, 2016

RGCB invites applications for the following positions from Indian citizens with prescribed qualifications. Full details including job description, additional desirable qualifications, etc. are described below.

Code No. 1

Senior Manager (Bioinformatics Operations)

(To download application format, click here )

Scale of Pay

PB-3 Rs.15600-39100 + Grade Pay Rs.6600/-

Number of Positions

1 (General)

Minimum Qualifications

PhD in Bioinformatics, Biotechnology, Life Sciences or Computer Science applied to biological questions.
A minimum of 5 years documented experience in national or state government R&D centers or state and central universities.
Track record of research funding and peer reviewed publications.
Proficiency using statistical analysis software or libraries such as R or Matlab.
Experience with a general scripting language such as Python, Ruby, or Pearl
Experience working with Next Generation Sequencing data
Proficiency with data visualization tools (Spotfire, Tableau, R, Python, etc.)
Experience with an object-oriented language such as Java, C++ or C# and familiarity with standard software development best practices: source code control, unit testing, in-code documentation and automated build environments.
Excellent listening, time management, organizational and interpersonal skills
Excellent communication skills, including the ability to illustrate problems and generate solutions
Management skills – demonstrated through the successful management of a team or large projects.
Broad and deep knowledge of computational methods for high-throughput sequence analysis and interpretation.
Extensive experience in delivering bioinformatics as a service and conducting training programs.
Experience of working with a production, customer-focused environment and business development projects.
Experience with management of funding and financial sustainability.
Demonstrated ability to work in a team environment and ability to lead and motivate an effective team, and also work as a good team player.
Good problem solver, able to logically identify solutions to technical problems.
Able to see the bigger picture and contribute towards strategic direction of Platforms and Pipelines teams.
Responsibilities

This position will involve cross-functional teamwork to build and develop bioinformatics tools and provide analysis for ongoing clinical trials.
Collaborate with biomarker scientists, clinical investigators and pipeline teams to build analytical tools.
Implement and evaluate new algorithms for R&D.
Support Research and Development teams by analyzing NGS data to identify predictive response markers
Lead training programs in Computational Biology and Bioinformatics.

More at http://rgcb.res.in/positions.php

Address of the bookmark: https://github.com/SysBioChalmers/RAVEN

Duration : Initially for a period of one year. Extendable based on the performance.

Qualification: (i) MSc in Bioinformatics, Biotechnology, Physics, Biophysics, Biochemistry,Computer Science with NET (UGC/CSIR/GATE/BINC/INSPIRE etc) qualification. (OR) (ii) M. Tech in Bioinformatics, Biotechnology

Additional qualification: Programming skills

Candidates who fulfill the requirements of IIT have the possibility to register for PhD.

Fellowship: Rs.25,000 and HRA.

Applicants are encouraged to send the CV to the coordinator by postal mail and e-mail. The deadline to receive the applications is 31st August 2016. The project coordinator has the discretion to restrict the number of candidates to be called for interview to a reasonable limit on the basis of qualifications and experience higher than the minimum prescribed in the announcement.

Project Co-ordinator:

Dr. M. Michael Gromiha
Department of Biotechnology
Indian Institute of Technology Madras
Chennai 600036
Email: gromiha@iitm.ac.in

11/3/2019: V 0.61, Improve graphical visualization (thanks to reviewers). Interactive networks and much more.

5/20/2019: V.0.60, Annotation database updated to Ensembl 96. New bacterial and fungal genomes based on STRING-db! Just paste your gene list to get enriched GO terms and othe pathways for over 315 plant and animal species, based on annotation from Ensembl (Release 96), Ensembl plants (R. 43) and Ensembl Metazoa (R. 43). An additional 2031 genomes (including bacteria and fungi) are annotated based on STRING-db (v.10). In addition, it also produces KEGG pathway diagrams with your genes highlighted, hierarchical clustering trees and networks summarizing overlapping terms/pathways, protein-protein interaction networks, gene characterristics plots, and enriched promoter motifs. 

Address of the bookmark: http://bioinformatics.sdstate.edu/go/

More at http://www.web.manit.ac.in/Year%202016/JRF/walk%20in.pdf

1. the ontology itself, which is a set of terms with their precise definitions and defined relationships between them, and
2. the associations between gene products and GO terms, which are used to capture the existing knowledge about what each gene is known to do.

But the term gene ontology, or GO, is commonly used to refer to both, which is sometimes a source of potential confusion. In order to avoid this, here we will use the term “GO ontology” to describe the set of terms and their hierarchical structure and “GO annotations” to describe the set of associations between genes and GO terms.

There are 3 types of terms, or domains if you wish, in the gene ontology:

• Biological Processes (BP)
• Molecular Functions (MF)
• Cellular Components (CC)

Address of the bookmark: https://advaitabio.com/faq-items/understanding-gene-ontology/